Method for supplementing points on granary wall boundary of irregular grain pile point cloud graph of granary

Abstract

The invention relates to a method for supplementing points on a granary wall boundary of a granary irregular grain pile point cloud graph, and the method comprises the following steps: S1, inputting basic parameters of a warehouse, and inputting the type and size of the warehouse; s2, grain pile point cloud data are read, and a point cloud graph is translated; s3, measuring points close to the bin wall area are extracted; and S4, supplementing the measuring points on the boundary of the silo wall according to a principle of proximity. The invention relates to the technical field of granary measurement. According to the method, the actual granary is combined, the measuring points on the granary wall boundary of the irregular grain pile point cloud graph are supplemented according to the principle of proximity, the point supplementing problem on the granary wall boundary of the irregular grain pile point cloud graph in the granary is effectively solved, the supplemented boundary measuring points are well matched with the grain pile, support is provided for an irregular grain pile volume algorithm based on point cloud data, and the method is suitable for large-scale popularization and application. The volume algorithm is higher in precision, simple in algorithm program principle, low in complexity, easy to understand and realize programming, reliable in result and beneficial to promotion of popularization and application of the laser radar technology in the grain industry and enforcement of the grain industry.

Description

Technical Field

[0001] The invention relates to the technical field of granary measurement, and in particular to a method for filling points on a granary wall boundary of a point cloud graph of an irregular grain pile in a granary. Background Art

[0002] In recent years, LiDAR technology has developed rapidly. The price of ordinary LiDAR sensors has dropped to around RMB 1,000, entering the stage of commercialization and civilian popularization, which has also brought new development opportunities to many disciplines and industries. It has been widely recognized that laser point cloud data has important application value.

[0003] The bulk grain piles during the operation of entering and leaving the granary are irregular and complex in shape. Accurately counting the number of irregular bulk grain piles in the granary has always been a technical problem in the grain industry and needs to be solved urgently. The traditional manual measurement method is backward in technology, time-consuming and labor-intensive, and has large measurement errors, which cannot meet actual needs. The volume of the grain pile multiplied by the average density of the grain pile gives the grain quantity (weight). Obviously, the high-precision volume algorithm for irregular bulk grain piles is the key to solving this problem. The algorithm is based on point cloud graphics.

[0004] The grain silo point cloud graphics obtained by scanning the laser radar three-dimensional measurement device mainly include the silo roof, silo wall and grain pile. The volume algorithm needs to extract the grain pile surface measurement points from the silo point cloud graphics to participate in the volume calculation, while the silo wall and silo roof measurement points should not participate in the volume calculation. The grain pile and the silo wall are generally in contact, and the silo wall can be used as the boundary of the grain pile. The elimination method is used to obtain the grain pile surface measurement points, and the grain pile is the remaining after eliminating the silo wall and silo roof. In order to eliminate the silo wall measurement points, considering that the silo wall and the grain pile are in contact, the silo wall is retracted a certain distance as the boundary, and the measurement points beyond the boundary are regarded as silo wall measurement points and eliminated.

[0005] However, in this method, the measurement points of the grain pile on the boundary of the silo wall are eliminated and need to be supplemented, otherwise it will affect the result of the volume algorithm. The grain pile in the silo is generally irregular, with ups and downs on the boundary and large height difference. Therefore, it is more difficult to supplement the measurement points on the boundary of the silo wall. Traditional point cloud processing methods are mostly general algorithms, which are not suitable for the above scenarios. For this reason, the present invention proposes a method for supplementing points on the boundary of the silo wall of the point cloud graphics of irregular grain piles in the silo, which provides support for the volume algorithm of irregular grain piles based on point cloud data, and makes the volume algorithm more accurate. Summary of the invention

[0006] In view of the deficiencies in the prior art, the purpose of the present invention is to provide a method for filling points on the boundary of a silo wall of a point cloud graphic of an irregular grain pile in a silo, so as to solve the above technical problems.

[0007] The above technical objectives of the present invention are achieved through the following technical solutions:

[0008] A method for filling points on the boundary of a grain silo point cloud graph of an irregular grain pile, comprising the following steps:

[0009] S1. Enter the basic parameters of the warehouse, including the type and size of the warehouse;

[0010] S2, reading grain pile point cloud data and performing translation processing on the point cloud graphics;

[0011] S3, extracting the measuring points close to the warehouse wall area;

[0012] S4. Supplement the measuring points on the warehouse wall boundary according to the principle of proximity.

[0013] Furthermore, in step S1, the warehouse types include flat warehouses and silos;

[0014] The warehouse dimensions of a flat warehouse include the length and width of the warehouse;

[0015] The chamber size of a silo is the chamber diameter.

[0016] Furthermore, in step S2, for a flat warehouse, a plane rectangular coordinate system is established with the lower left corner of the warehouse as the origin, so that the lower left corner point of the warehouse in the point cloud graphic is located at the origin of the coordinate system;

[0017] For the silo, a plane rectangular coordinate system is established with the center of the warehouse as the origin, so that the center of the warehouse in the point cloud graphics is located at the origin of the coordinate system.

[0018] Furthermore, the bungalow warehouse includes four walls, namely, a left transverse wall, a right transverse wall, a lower longitudinal wall and an upper longitudinal wall. The boundary conditions for extracting the measuring points of each wall near the warehouse wall area are:

[0019] Left horizontal wall: |x|≤Δs

[0020] Right transverse wall: |xL|≤Δs

[0021] Lower longitudinal wall: |y|≤Δs

[0022] Upper longitudinal wall: |yW|≤Δs

[0023] Where x and y are the horizontal and vertical coordinates of the measuring point close to the warehouse wall, L is the length of the warehouse, W is the width of the warehouse, and Δs is the inward shrinkage distance of the wall.

[0024] Furthermore, the boundary conditions of the measuring points of the silo near the silo wall area are:

[0025] |dr|≤Δr

[0026]

[0027] Where x and y are the horizontal and vertical coordinates of the measuring point close to the warehouse wall, d is the distance from the measuring point close to the warehouse wall to the origin of the coordinate system, r is the radius of the warehouse, and Δr is the inward retraction distance of the warehouse wall.

[0028] Furthermore, the specific method of applying step S4 to a flat warehouse is:

[0029] Fill in points along the boundaries of the four walls, add a boundary point at a certain interval, and the number of supplementary measurement points on each wall boundary is calculated as follows:

[0030] n=l / Δl

[0031] Where n is the number of supplementary boundary measurement points, l is the length of the wall, and Δl is the distance between the measurement points;

[0032] According to the principle of proximity, several adjacent points of each boundary point are found from the measurement points close to the warehouse wall area. The query conditions are as follows:

[0033] Left and right transverse walls: |yy w |≤s

[0034] Lower longitudinal wall and upper longitudinal wall: |xx w |≤s

[0035] In the above formula, x and y are the horizontal and vertical coordinates of the measuring point close to the warehouse wall area, respectively. w and w are the horizontal and vertical coordinates of the boundary measuring point, respectively, and s is the allowable value of distance deviation;

[0036] The height calculation formula of the boundary measuring point is as follows:

[0037]

[0038] In the above formula, z w is the height of the boundary measurement point, is the average height of all adjacent measuring points, n is the total number of adjacent measuring points of the boundary measuring point, z i is the height of the i-th adjacent measuring point.

[0039] Furthermore, the specific method of applying step S4 to the silo is:

[0040] Fill in points along the warehouse wall boundary, add a boundary point at a certain angle, and the number of supplementary measurement points on the warehouse wall boundary (circumference) is calculated as follows:

[0041] n=360 / Δα

[0042] In the above formula, n is the number of supplementary boundary measuring points, and Δα is the angle interval value of the measuring points;

[0043] The coordinates of the boundary measurement points and the measurement points near the warehouse wall are converted from spatial rectangular coordinates to cylindrical coordinates (r, θ, z);

[0044] According to the principle of proximity, several adjacent points of each boundary point are found from the measurement points close to the warehouse wall area. The query conditions are as follows:

[0045] |θ-θ w |≤β

[0046] In the above formula, θ is the angle of the measuring point close to the warehouse wall area, θ w is the angle of the measuring point on the warehouse wall boundary, and β is the allowable value of the angle deviation;

[0047] The height calculation formula of the boundary measuring point is as follows:

[0048]

[0049] In the above formula, z w is the height of the boundary measurement point, is the average height of all adjacent measuring points, n is the total number of adjacent measuring points of the boundary measuring point, z i is the height of the i-th adjacent measuring point.

[0050] In summary, the present invention includes at least one of the following beneficial technical effects:

[0051] 1. The present invention combines the actual situation of the granary and supplements the measuring points on the boundary of the silo wall of the point cloud graphics of the irregular grain pile in the granary according to the principle of proximity, which effectively solves the problem of supplementing points on the boundary of the silo wall of the point cloud graphics of the irregular grain pile in the granary. The supplemented boundary measuring points are well consistent with the shape of the grain pile, providing support for the volume algorithm of the irregular grain pile based on point cloud data, making the volume algorithm more accurate.

[0052] 2. The algorithm program in the present invention has a simple principle, low complexity, is easy to understand and program, and has reliable results. It is conducive to promoting the popularization and application of lidar technology in the grain industry, empowering the grain industry, and improving the level of informatization and intelligent technology in the grain industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 is a flow chart of the present invention;

[0054] Figure 2 This is a schematic diagram of the area near the warehouse wall of the bunk house in the present invention;

[0055] Figure 3 is a schematic diagram of the area of ​​the silo close to the silo wall in the present invention;

[0056] Figure 4 It is a three-dimensional point cloud diagram of the grain pile in the silo of the present invention.

[0057] In the figure, 1. Left horizontal wall of bungalow warehouse; 2. Right horizontal wall of bungalow warehouse; 3. Lower vertical wall of bungalow warehouse; 4. Upper vertical wall of bungalow warehouse; 5. Silo wall. DETAILED DESCRIPTION

[0058] In order to more clearly illustrate the overall concept of the present invention, a detailed description is given below in an exemplary manner in conjunction with the accompanying drawings.

[0059] The invention discloses a method for filling points on a silo wall boundary of a point cloud graph of an irregular grain pile in a silo. Combined with the actual situation of the silo, the method supplements the measuring points on the silo wall boundary of the point cloud graph of the irregular grain pile in the silo according to the principle of proximity.

[0060] First, select the measurement points close to the warehouse wall area from the grain pile point cloud graphics; second, add a boundary point at a certain distance or angle along the warehouse wall boundary to determine the plane coordinates of the boundary point; then select the adjacent points of the boundary point from the measurement points close to the warehouse wall area according to the principle of proximity, and finally, take the average height of the adjacent points as the height of the boundary point to determine the z coordinate of the boundary. In this way, the three-dimensional coordinates of each boundary point are finally determined.

[0061] Embodiment 1:

[0062] Reference Figure 1 and Figure 2 The type of granary is a flat granary. The method for filling points on the granary wall boundary of the point cloud graph of irregular grain pile in a flat granary includes the following steps:

[0063] S1. Enter the basic parameters of the warehouse, including the length and width of the warehouse.

[0064] S2. Read the grain pile point cloud data and perform translation processing on the point cloud graphics. Establish a plane rectangular coordinate system with the lower left corner of the warehouse as the origin, so that the lower left corner point of the warehouse in the point cloud graphics is located at the origin of the coordinate system.

[0065] S3. Extract measurement points close to the warehouse wall area.

[0066] The bungalow warehouse includes four walls: left horizontal wall, right horizontal wall, lower longitudinal wall and upper longitudinal wall. The boundary conditions for extracting the measuring points of each wall near the warehouse wall area are:

[0067] Left horizontal wall: |x|≤Δs

[0068] Right transverse wall: |xL|≤Δs

[0069] Lower longitudinal wall: |y|≤Δs

[0070] Upper longitudinal wall: |yW|≤Δs

[0071] Where x and y are the horizontal and vertical coordinates of the measuring point close to the warehouse wall, L is the length of the warehouse, W is the width of the warehouse, and Δs is the inward shrinkage distance of the wall.

[0072] S4. Supplement the measuring points on the warehouse wall boundary according to the principle of proximity.

[0073] The specific method of applying step S4 to a flat warehouse is:

[0074] Fill in points along the boundaries of the four walls, add a boundary point at a certain interval, and the number of supplementary measurement points on each wall boundary is calculated as follows:

[0075] n=l / Δl

[0076] Where n is the number of supplementary boundary measurement points, l is the length of the wall, and Δl is the distance between the measurement points;

[0077] According to the principle of proximity, several adjacent points of each boundary point are found from the measurement points close to the warehouse wall area. The query conditions are as follows:

[0078] Left and right transverse walls: |yy w |≤s

[0079] Lower longitudinal wall and upper longitudinal wall: |xx w |≤s

[0080] In the above formula, x and y are the horizontal and vertical coordinates of the measuring point close to the warehouse wall area, respectively. w and w are the horizontal and vertical coordinates of the boundary measuring point, respectively, and s is the allowable value of distance deviation;

[0081] The height calculation formula of the boundary measuring point is as follows:

[0082]

[0083] In the above formula, z w is the height of the boundary measurement point, is the average height of all adjacent measuring points, n is the total number of adjacent measuring points of the boundary measuring point, z i is the height of the i-th adjacent measuring point.

[0084] Using Python programming language, the corresponding calculation program was written according to the above steps.

[0085] Embodiment 2:

[0086] In this embodiment, a grain warehouse is selected to apply the algorithm in Embodiment 1, so as to verify the accuracy of the algorithm in Embodiment 1.

[0087] The warehouse is 29090mm long and 19450mm wide. The point cloud data of the grain warehouse is collected using a laser radar 3D scanning measurement device.

[0088] S21. Enter the basic parameters of the warehouse. The warehouse type is flat warehouse, the length is 29090mm, and the width is 19450mm.

[0089] S22, reading the grain pile point cloud data, and performing translation processing on the point cloud graphics.

[0090] S23, extracting measuring points close to the warehouse wall area. The inward shrinkage distance Δs of the surrounding walls is set to 1000 mm, and the algorithm of step S3 in Example 1 is used to extract measuring points close to the surrounding wall area from the grain pile point cloud graphics.

[0091] S24, supplement the measuring points on the warehouse wall boundary. Supplement the points according to the principle of proximity, take the boundary point spacing as 500mm, calculate the number of measuring points on each wall boundary, and determine the plane coordinates of the boundary measuring points. Then find the adjacent measuring points of each boundary point and calculate the height of the boundary point. Finally, the three-dimensional coordinates (x w ,y w ,z w ) are all determined.

[0092] Finally, after the grain pile point cloud graphics were supplemented with boundaries, the heights of the boundary points and adjacent points were close, with no obvious distortion, indicating that the supplemented point results were reliable.

[0093] Embodiment 3:

[0094] Reference Figure 1 and Figure 3 , the type of granary is silo. The method of filling points on the silo wall boundary of the irregular grain pile point cloud graphics of the silo includes the following steps:

[0095] S1. Enter the basic parameters of the warehouse, including the diameter of the warehouse.

[0096] S2. Establish a plane rectangular coordinate system with the warehouse center as the origin, so that the warehouse center in the point cloud graphics is located at the origin of the coordinate system.

[0097] S3. The boundary conditions of the measuring point near the silo wall are:

[0098] |dr|≤Δr

[0099]

[0100] Where x and y are the horizontal and vertical coordinates of the measuring point close to the warehouse wall, d is the distance from the measuring point close to the warehouse wall to the origin of the coordinate system, r is the radius of the warehouse, and Δr is the inward retraction distance of the warehouse wall.

[0101] The specific method of applying step S4 to the silo is:

[0102] Fill in points along the warehouse wall boundary, add a boundary point at a certain angle, and the number of supplementary measurement points on the warehouse wall boundary (circumference) is calculated as follows:

[0103] n=360 / Δα

[0104] In the above formula, n is the number of supplementary boundary measuring points, and Δα is the angle interval value of the measuring points;

[0105] The coordinates of the boundary measurement points and the measurement points near the warehouse wall are converted from spatial rectangular coordinates to cylindrical coordinates (r, θ, z);

[0106] According to the principle of proximity, several adjacent points of each boundary point are found from the measurement points close to the warehouse wall area. The query conditions are as follows:

[0107] |θ-θ w |≤β

[0108] In the above formula, θ is the angle of the measuring point close to the warehouse wall area, θ w is the angle of the measuring point on the warehouse wall boundary, and β is the allowable value of the angle deviation;

[0109] The height calculation formula of the boundary measuring point is as follows:

[0110]

[0111] In the above formula, z w is the height of the boundary measurement point, is the average height of all adjacent measuring points, n is the total number of adjacent measuring points of the boundary measuring point, z i is the height of the i-th adjacent measuring point.

[0112] Using Python programming language, the corresponding calculation program was written according to the above steps.

[0113] Embodiment 4:

[0114] Reference Figure 4 In this embodiment, a grain silo is selected to apply the algorithm in Example 3 to verify the accuracy of the algorithm in Example 3.

[0115] The warehouse diameter is 27290mm.

[0116] S31. Enter the basic parameters of the warehouse. The warehouse type is silo and the warehouse radius is 13645mm.

[0117] S32, read grain pile point cloud data (such as Figure 4 As shown in the figure), and translate the point cloud graphics.

[0118] S33, extracting measuring points close to the warehouse wall area. The inward shrinkage distance Δr of the surrounding walls is set to 500 mm, and the algorithm of step S3 in Example 3 is used to extract measuring points close to the surrounding wall area from the grain pile point cloud graphics.

[0119] S34, supplement the measuring points on the warehouse wall boundary. Supplement the points according to the principle of proximity, and take the boundary point interval angle of 1 degree. Calculate the number of measuring points on the warehouse wall boundary to determine the plane coordinates of the boundary measuring points. Then perform coordinate conversion on the boundary points and the measuring points close to the warehouse wall area, from spatial rectangular coordinates to cylindrical coordinates, and then find the adjacent measuring points of each boundary point, and calculate the height of the boundary point. Finally, the cylindrical coordinates and spatial rectangular coordinates (x w ,y w ,z w ) are all determined.

[0120] Finally, the grain pile point cloud graphics supplemented the silo wall boundary points and the grain pile shape is consistent, the boundary points and the adjacent points are close in height, and there is no obvious distortion, indicating that the supplemented point results are reliable.

[0121] The implementation principle of the above embodiment is:

[0122] The present invention combines the actual situation of the granary and supplements the measuring points on the boundary of the silo wall of the point cloud graphics of the irregular grain pile in the granary according to the principle of proximity. First, the measuring points close to the silo wall area are selected from the grain pile point cloud graphics; secondly, a boundary point is supplemented at a certain distance or angle along the boundary of the silo wall to determine the plane coordinates of the boundary point; then, the adjacent points of the boundary point are selected from the measuring points close to the silo wall area according to the principle of proximity, and finally, the average height of the adjacent points is used as the height of the boundary point to determine the z coordinate of the boundary. In this way, the three-dimensional coordinates of each boundary point are finally determined, which effectively solves the problem of supplementing points on the boundary of the silo wall of the point cloud graphics of the irregular grain pile in the granary. The supplemented boundary measuring points are in good agreement with the grain pile shape, which provides support for the irregular grain pile volume algorithm based on point cloud data, making the volume algorithm more accurate.

[0123] The embodiments of this specific implementation method are all preferred embodiments of the present invention, and are not intended to limit the protection scope of the present invention. Therefore, any equivalent changes made based on the structure, shape, and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for filling points on the boundary of a grain silo point cloud graph of an irregular grain pile, characterized by: The following steps are involved: S1. Enter the basic parameters of the warehouse, including the type and size of the warehouse; S2, reading grain pile point cloud data and performing translation processing on the point cloud graphics; S3, extracting the measuring points close to the warehouse wall area; S4. Supplement the measuring points on the warehouse wall boundary according to the principle of proximity.

2. The method for filling points on the boundary of the grain silo wall of the point cloud graph of irregular grain pile in a grain silo according to claim 1, characterized in that: In step S1, the warehouse types include flat warehouses and silos; The warehouse dimensions of a flat warehouse include the length and width of the warehouse; The chamber size of a silo is the chamber diameter.

3. The method for filling points on the boundary of the grain silo wall of the point cloud graph of irregular grain pile in a grain silo according to claim 2, characterized in that: In step S2, for a flat warehouse, a plane rectangular coordinate system is established with the lower left corner of the warehouse as the origin, so that the lower left corner point of the warehouse in the point cloud graph is located at the origin of the coordinate system; For the silo, a plane rectangular coordinate system is established with the center of the warehouse as the origin, so that the center of the warehouse in the point cloud graphics is located at the origin of the coordinate system.

4. The method for filling points on the boundary of the grain silo wall of the point cloud graph of irregular grain pile in a grain silo according to claim 3, characterized in that: The bungalow warehouse includes four walls: left horizontal wall, right horizontal wall, lower longitudinal wall and upper longitudinal wall. The boundary conditions for extracting the measuring points of each wall near the warehouse wall area are: Left horizontal wall: |x|≤Δs Right transverse wall: |xL|≤Δs Lower longitudinal wall: |y|≤Δs Upper longitudinal wall: |yW|≤Δs Where x and y are the horizontal and vertical coordinates of the measuring point close to the warehouse wall, L is the length of the warehouse, W is the width of the warehouse, and Δs is the inward shrinkage distance of the wall.

5. The method for filling points on the boundary of the grain silo wall of the point cloud graph of irregular grain pile in a grain silo according to claim 3, characterized in that: The boundary conditions of the measuring point near the silo wall are: |dr|≤Δr Where x and y are the horizontal and vertical coordinates of the measuring point close to the warehouse wall, d is the distance from the measuring point close to the warehouse wall to the origin of the coordinate system, r is the radius of the warehouse, and Δr is the inward retraction distance of the warehouse wall.

6. The method for filling points on the boundary of the grain silo wall of the point cloud graph of irregular grain pile in a grain silo according to claim 4, characterized in that: The specific method of applying step S4 to a flat warehouse is: Fill in points along the boundaries of the four walls, add a boundary point at a certain interval, and the number of supplementary measurement points on each wall boundary is calculated as follows: n=l / Δl Where n is the number of supplementary boundary measurement points, l is the length of the wall, and Δl is the distance between the measurement points; According to the principle of proximity, several adjacent points of each boundary point are found from the measurement points close to the warehouse wall area. The query conditions are as follows: Left and right transverse walls: |yy w |≤s Lower longitudinal wall and upper longitudinal wall: |xx w |≤s In the above formula, x and y are the horizontal and vertical coordinates of the measuring point close to the warehouse wall area, respectively. w and w are the horizontal and vertical coordinates of the boundary measuring point, respectively, and s is the allowable value of distance deviation; The height calculation formula of the boundary measuring point is as follows: In the above formula, z w is the height of the boundary measurement point, is the average height of all adjacent measuring points, n is the total number of adjacent measuring points of the boundary measuring point, z i is the height of the i-th adjacent measuring point.

7. The method for filling points on the boundary of the grain silo wall of the point cloud graph of irregular grain pile in a grain silo according to claim 5, characterized in that: The specific method of applying step S4 to the silo is: Fill in points along the warehouse wall boundary, add a boundary point at a certain angle, and the number of supplementary measurement points on the warehouse wall boundary (circumference) is calculated as follows: n=360 / Δα In the above formula, n is the number of supplementary boundary measuring points, and Δα is the angle interval value of the measuring points; The coordinates of the boundary measurement points and the measurement points near the warehouse wall are converted from spatial rectangular coordinates to cylindrical coordinates (r, θ, z); According to the principle of proximity, several adjacent points of each boundary point are found from the measurement points close to the warehouse wall area. The query conditions are as follows: |θ-θ w |≤β In the above formula, θ is the angle of the measuring point close to the warehouse wall area, θ w is the angle of the measuring point on the warehouse wall boundary, and β is the allowable value of the angle deviation; The height calculation formula of the boundary measuring point is as follows: In the above formula, z w is the height of the boundary measurement point, is the average height of all adjacent measuring points, n is the total number of adjacent measuring points of the boundary measuring point, z i is the height of the i-th adjacent measuring point.

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